Segmentation based building detection in high resolution satellite images

Prajowal Manandhar, Zeyar Aung, Prashanth Marpu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

We demonstrate an integrated strategy for identifying buildings in very high resolution satellite imagery of urban areas. Buildings are extracted using structural, contextual, and spectral information. We perform multi-resolution and spectral difference segmentation to obtain a proper object segmentation. First, we use One-Class support vector machine (SVM) in order to determine the man-made structures (buildings, roads, etc.). Next, we proceed with texture segmentation approach using a conditional threshold value to extract the buildings. And then, we use geodesic opening and closing operations to extract bright foreground objects. After this, shadows and vegetation regions are detected in these segments based on their spectral properties. We then remove noise, vegetation and shadows from the candidate building regions. And finally, we classify the buildings by checking for the presence of shadows along the buildings opposite to the sun's azimuth direction to distinguish buildings from other bright regions. Performance evaluation of the proposed algorithm is performed on data acquired using WorldView satellite imagery over Abu Dhabi, United Arab Emirates.

Original languageBritish English
Title of host publication2017 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publicationInternational Cooperation for Global Awareness, IGARSS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3783-3786
Number of pages4
ISBN (Electronic)9781509049516
DOIs
StatePublished - 1 Dec 2017
Event37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 - Fort Worth, United States
Duration: 23 Jul 201728 Jul 2017

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2017-July

Conference

Conference37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Country/TerritoryUnited States
CityFort Worth
Period23/07/1728/07/17

Keywords

  • Building Candidate
  • Building Detection
  • Image Segmentation
  • One-Class SVM
  • Supervised Learning

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